Using data clustering to reveal trainees’ behavior in
cybersecurity education

J 2024

Using data clustering to reveal trainees’ behavior in cybersecurity education

DOČKALOVÁ BURSKÁ, Karolína; Jakub Rudolf MLYNÁRIK a Radek OŠLEJŠEK

Základní údaje

Originální název

Using data clustering to reveal trainees’ behavior in cybersecurity education

Autoři

DOČKALOVÁ BURSKÁ, Karolína; Jakub Rudolf MLYNÁRIK a Radek OŠLEJŠEK

Vydání

Education and Information Technologies, Springer, 2024, 1360-2357

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Article

Impakt faktor

Impact factor: 5.400

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/24:00135510

Organizační jednotka

Fakulta informatiky

Klíčová slova anglicky

visual analytics; clustering analysis; hands-on learning; visualization

Příznaky

Recenzováno

Změněno: 4. 4. 2025 11:10, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

In cyber security education, hands-on training is a common type of exercise to help raise awareness and competence, and improve students' cybersecurity skills. To be able to measure the impact of the design of the particular courses, the designers need methods that can reveal hidden patterns in trainee behavior. However, the support of the designers in performing such analytic and evaluation tasks is ad-hoc and insufficient. With unsupervised machine learning methods, we designed a tool for clustering the trainee actions that can exhibit their strategies or help pinpoint flaws in the training design. By using a \emph{k-means++} algorithm, we explore clusters of trainees that unveil their specific behavior within the training sessions. The final visualization tool consists of views with scatter plots and radar charts. The former provides a two-dimensional correlation of selected trainee actions and displays their clusters. In contrast, the radar chart displays distinct clusters of trainees based on their more specific strategies or approaches when solving tasks. Through iterative training redesign, the tool can help designers identify improper training parameters and improve the quality of the courses accordingly. To evaluate the tool, we performed a qualitative evaluation of its outcomes with cybersecurity experts. The results confirm the usability of the selected methods in discovering significant trainee behavior. Our insights and recommendations can be beneficial for the design of tools for educators, even beyond cyber security.

Návaznosti

CZ.02.1.01/0.0/0.0/16_019/0000822, interní kód MU
(Kód CEP: EF16_019/0000822)

Název: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur (Akronym: C4e)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur, PO 1 Posilování kapacit pro kvalitní výzkum

EF16_019/0000822, projekt VaV

Název: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur

Přiložené soubory

2024-using-data-clustering-reveal-trainees-behavior-cybersecurity-education-paper.pdf

Citovat

DOČKALOVÁ BURSKÁ, Karolína; Jakub Rudolf MLYNÁRIK a Radek OŠLEJŠEK. Using data clustering to reveal trainees’ behavior in cybersecurity education. Education and Information Technologies. Springer, 2024, roč. 29, č. 13, s. 16613-16639. ISSN 1360-2357. Dostupné z: https://doi.org/10.1007/s10639-024-12480-x.

@article{2373677,
   author = {Dočkalová Burská, Karolína and Mlynárik, Jakub Rudolf and Ošlejšek, Radek},
   article_number = {13},
   doi = {https://doi.org/10.1007/s10639-024-12480-x},
   keywords = {visual analytics; clustering analysis; hands-on learning; visualization},
   language = {eng},
   issn = {1360-2357},
   journal = {Education and Information Technologies},
   title = {Using data clustering to reveal trainees’ behavior in cybersecurity education},
   url = {https://doi.org/10.1007/s10639-024-12480-x},
   volume = {29},
   year = {2024}
}

TY  - JOUR
ID  - 2373677
AU  - Dočkalová Burská, Karolína - Mlynárik, Jakub Rudolf - Ošlejšek, Radek
PY  - 2024
TI  - Using data clustering to reveal trainees’ behavior in cybersecurity education
JF  - Education and Information Technologies
VL  - 29
IS  - 13
SP  - 16613-16639
EP  - 16613-16639
PB  - Springer
SN  - 13602357
KW  - visual analytics
KW  - clustering analysis
KW  - hands-on learning
KW  - visualization
UR  - https://doi.org/10.1007/s10639-024-12480-x
N2  - In cyber security education, hands-on training is a common type of exercise to help raise awareness and competence, and improve students' cybersecurity skills. To be able to measure the impact of the design of the particular courses, the designers need methods that can reveal hidden patterns in trainee behavior. However, the support of the designers in performing such analytic and evaluation tasks is ad-hoc and insufficient. With unsupervised machine learning methods, we designed a tool for clustering the trainee actions that can exhibit their strategies or help pinpoint flaws in the training design. By using a \emph{k-means++} algorithm, we explore clusters of trainees that unveil their specific behavior within the training sessions. The final visualization tool consists of views with scatter plots and radar charts. The former provides a two-dimensional correlation of selected trainee actions and displays their clusters. In contrast, the radar chart displays distinct clusters of trainees based on their more specific strategies or approaches when solving tasks. Through iterative training redesign, the tool can help designers identify improper training parameters and improve the quality of the courses accordingly. To evaluate the tool, we performed a qualitative evaluation of its outcomes with cybersecurity experts. The results confirm the usability of the selected methods in discovering significant trainee behavior. Our insights and recommendations can be beneficial for the design of tools for educators, even beyond cyber security.
ER  -

DOČKALOVÁ BURSKÁ, Karolína; Jakub Rudolf MLYNÁRIK a Radek OŠLEJŠEK. Using data clustering to reveal trainees’ behavior in cybersecurity education. \textit{Education and Information Technologies}. Springer, 2024, roč.~29, č.~13, s.~16613-16639. ISSN~1360-2357. Dostupné z: https://doi.org/10.1007/s10639-024-12480-x.

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